Results for “exa”

Use this skill when the user asks about Americans with Disabilities Act (ADA) accommodation for CDL drivers — interaction between ADA + FMCSA medical certification, when DOT-disqualifying conditions trigger ADA analysis, reasonable accommodation case examples, employer obligations, and how to handle a driver with a condition that may affect CDL status. Cite Title I ADA + 49 CFR 391.41.

Build a composable CLI for Codex from API docs, an OpenAPI spec, existing curl examples, an SDK, a web app, an admin tool, or a local script. Use when the user wants Codex to create a command-line tool that can run from any repo, expose composable read/write commands, return stable JSON, manage auth, and pair with a companion skill.

This skill should be used when the user asks to "understand a codebase", "get code context", "research a library", "explore a repository", "find code examples", "look up documentation", asks a natural-language code/technology question (e.g. "how does X work", "X vs Y", "best practice for Z"), or wants to understand how a specific project, library, or concept works before making changes.

Drafts a Written Information Security Program compliant with Massachusetts 201 CMR 17.00 and supplementary frameworks (GDPR, CCPA, HIPAA, GLBA, PCI-DSS). Produces a board-ready regulatory document covering coordinator designation, risk assessment, safeguards, training, incident response with breach notification, and vendor oversight. Use when an organization handles personal information of MA residents and needs a standalone WISP for regulatory examination or executive approval.

Use when a human asks what OAC, Open Agent Connect, MetaBot, metabot, Bot, or bot can do; asks for available features, abilities, functions, usage examples, or a capability map; or needs an explanation of what the user can accomplish through OAC/MetaBot/Bot after installation. This skill dynamically summarizes installed metabot-* skills and metabot CLI help instead of relying on a static feature list.

Guides attorneys through deposition witness preparation using a two-session model with document review, practice examination, and day-of logistics. Covers party witnesses, fact witnesses, 30(b)(6) corporate representatives, and experts. Produces preparation memos, document review lists, topic summaries, and day-of checklists. Enforces ABA Opinion 508 ethical boundaries. Use when preparing any witness for deposition, scheduling prep sessions, or building witness preparation materials.

High-fidelity website/app clone design pipeline. Use when asked to clone, replicate, copy, or recreate any existing website or app screen. Captures real assets (images, SVGs, fonts, colors), extracts exact design tokens, generates the clone in Stitch, composites real assets into the output, then runs section-by-section visual comparison against the reference. Produces 90%+ accurate clones by combining Stitch generation with real asset injection.

Shorthand-first response compression that cuts ~40% of response tokens while preserving technical precision and exact literals. Use when the user says "steno mode", "shorthand mode", "compressed responses", "token reduction", "brief structured output", or invokes /steno. Supports four compression levels: lite, brief, court, machine. Do not trigger for requests needing polished prose such as onboarding/tutorial content, stakeholder or customer-facing copy, or teaching-focused explanations.

Search a codebase or UI for places that don't animate but should, and reject everything that shouldn't. Read-only; it proposes motion with exact values, it does not implement it. Use when the user asks "what could be animated here?" or wants to "make this feel more alive". For fixing existing animations, use `improve-animations` or `review-animations` instead. Source: github.com/emilkowalski/skills.

Semantic-search personal knowledge (memory, plans, handoffs, skills, Codex rules) via the local RAG index at ~/.claude/rag-index/. Use when a query is fuzzy or cross-file ("how did we fix X", "what did we decide about Y", "which skill handles Z"). Complements grep (exact) and Serena (code symbols). If the user asks a recall question that doesn't map to a specific known file, reach here first.

JACKAL — First Jump pyramider. FOX v1.6's exact five-layer entry gauntlet combined with RHINO's pyramiding mechanic. Enter at 30% on a qualifying First Jump, add 40% at +10% ROE and final 30% at +20% ROE — but only after re-validating 4h trend, SM alignment, and volume. Failed scouts cost $15 instead of FOX's $50. Full pyramids capture the same upside. DSL High Water Mode (mandatory).

Systematic API design methodology with 6 validated patterns covering parameter categorization, safe refactoring, audit-first approach, automated validation, quality gates, and example-driven documentation. Use when designing new APIs, improving API consistency, implementing breaking change policies, or building API quality enforcement. Provides deterministic decision trees (5-tier parameter system), validation tool architecture, pre-commit hook patterns. Validated with 82.5% cross-domain transferability, 37.5% efficiency gains through audit-first refactoring.

Use when creating new Excalidraw diagrams or reading, modifying, or comparing existing .excalidraw or .excalidraw.json files. Also use when the user asks for hand-drawn style diagrams, whiteboard sketches, architecture diagrams in Excalidraw format, or wants to export Excalidraw to SVG/PNG. Use this skill even if the user doesn't say "Excalidraw" — for example when they ask for a system diagram, flowchart, or architecture sketch that should look hand-drawn or informal.

Use this skill when working with symbolic mathematics in Python. This skill should be used for symbolic computation tasks including solving equations algebraically, performing calculus operations (derivatives, integrals, limits), manipulating algebraic expressions, working with matrices symbolically, physics calculations, number theory problems, geometry computations, and generating executable code from mathematical expressions. Apply this skill when the user needs exact symbolic results rather than numerical approximations, or when working with mathematical formulas that contain variables and parameters.

GraphQL gives clients exactly the data they need - no more, no less. One endpoint, typed schema, introspection. But the flexibility that makes it powerful also makes it dangerous. Without proper controls, clients can craft queries that bring down your server. This skill covers schema design, resolvers, DataLoader for N+1 prevention, federation for microservices, and client integration with Apollo/urql. Key insight: GraphQL is a contract. The schema is the API documentation. Design it carefully.

GraphQL gives clients exactly the data they need - no more, no less. One endpoint, typed schema, introspection. But the flexibility that makes it powerful also makes it dangerous. Without proper controls, clients can craft queries that bring down your server. This skill covers schema design, resolvers, DataLoader for N+1 prevention, federation for microservices, and client integration with Apollo/urql. Key insight: GraphQL is a contract. The schema is the API documentation. Design it carefully.

GraphQL gives clients exactly the data they need - no more, no less. One endpoint, typed schema, introspection. But the flexibility that makes it powerful also makes it dangerous. Without proper controls, clients can craft queries that bring down your server. This skill covers schema design, resolvers, DataLoader for N+1 prevention, federation for microservices, and client integration with Apollo/urql. Key insight: GraphQL is a contract. The schema is the API documentation. Design it carefully.

Use this skill when working with symbolic mathematics in Python. This skill should be used for symbolic computation tasks including solving equations algebraically, performing calculus operations (derivatives, integrals, limits), manipulating algebraic expressions, working with matrices symbolically, physics calculations, number theory problems, geometry computations, and generating executable code from mathematical expressions. Apply this skill when the user needs exact symbolic results rather than numerical approximations, or when working with mathematical formulas that contain variables and parameters.

GraphQL gives clients exactly the data they need - no more, no less. One endpoint, typed schema, introspection. But the flexibility that makes it powerful also makes it dangerous. Without proper controls, clients can craft queries that bring down your server. This skill covers schema design, resolvers, DataLoader for N+1 prevention, federation for microservices, and client integration with Apollo/urql. Key insight: GraphQL is a contract. The schema is the API documentation. Design it carefully.

Use this skill when working with symbolic mathematics in Python. This skill should be used for symbolic computation tasks including solving equations algebraically, performing calculus operations (derivatives, integrals, limits), manipulating algebraic expressions, working with matrices symbolically, physics calculations, number theory problems, geometry computations, and generating executable code from mathematical expressions. Apply this skill when the user needs exact symbolic results rather than numerical approximations, or when working with mathematical formulas that contain variables and parameters.

GraphQL gives clients exactly the data they need - no more, no less. One endpoint, typed schema, introspection. But the flexibility that makes it powerful also makes it dangerous. Without proper controls, clients can craft queries that bring down your server. This skill covers schema design, resolvers, DataLoader for N+1 prevention, federation for microservices, and client integration with Apollo/urql. Key insight: GraphQL is a contract. The schema is the API documentation. Design it carefully.

Proposes exactly one personal side-project idea per invocation, sized to a 1-3 day MVP. Targets CLI, automation, LLM, DX, productivity, and data-viz angles; avoids clichés like TODO apps, weather apps, and pomodoro timers. Output is an 8-section brief including a ready-to-paste coding-agent prompt. Use for morning/daily idea rituals and weekend-hack ideation. Don't use for existing-product feature proposals (Spark), dialogue brainstorming (Riff), or prototype implementation (Forge).

Expert knowledge for Azure Oracle development including troubleshooting, security, configuration, and integrations & coding patterns. Use when configuring TDE with Key Vault, Oracle@Azure connectivity, AI DB VNets, Exadata log export, or Sentinel, and other Azure Oracle related development tasks. Not for Azure SQL Database (use azure-sql-database), Azure SQL Managed Instance (use azure-sql-managed-instance), SQL Server on Azure Virtual Machines (use azure-sql-virtual-machines), Azure VMware Solution (use azure-vmware-solution).

Use this skill when working with symbolic mathematics in Python. This skill should be used for symbolic computation tasks including solving equations algebraically, performing calculus operations (derivatives, integrals, limits), manipulating algebraic expressions, working with matrices symbolically, physics calculations, number theory problems, geometry computations, and generating executable code from mathematical expressions. Apply this skill when the user needs exact symbolic results rather than numerical approximations, or when working with mathematical formulas that contain variables and parameters.

Teleological physiology analysis framework for understanding biological systems through multi-constraint optimization. Use when analyzing physiological mechanisms, explaining apparent biological "inefficiencies", preparing for medical examinations (CICM/ANZCA Primary), understanding why biological systems are designed the way they are, or when seeking deeper mechanistic understanding beyond descriptive knowledge. Triggers on questions like "why is X designed this way", "what purpose does Y serve", "how is Z optimized", analysis of physiological trade-offs, or exploration of evolutionary/design constraints.

Build throwaway code that answers exactly one design question — a tiny terminal app to feel out logic/state models, or several radically different UI variants switchable on one route. Use when the user wants to "prototype", "mock up", "sketch", "try a few versions", "see what it'd look like", "feel out this state machine", or is stuck choosing between designs they can only judge by seeing or driving them. Also used by the whiteboard skill for napkin-type tickets.

Reverse-lookup glossary that turns a vague description of a web animation or motion effect into its exact term ("the bouncy thing when a popover opens" → Pop in; "the iOS rubber-band scroll" → Rubber-banding). Use when the user asks "what's it called when…", or describes a motion effect without knowing its name and wants the right word to prompt an AI or designer with. For naming an effect, not designing or building one. Source: github.com/emilkowalski/skills.

When tackling a task that requires domain expertise beyond general coding ability — architecture patterns, framework-specific gotchas, deployment strategies, security anti-patterns, or specialized workflows — call the windags_skill_graft MCP tool with your task description. You'll receive expert knowledge including decision trees, failure modes, worked examples, and anti-patterns from a library of 503+ curated skills. Only graft when the task genuinely requires specialized knowledge. Simple tasks (rename a variable, fix a typo, format code) do not need grafting.

This skill suggests using approved weight‑loss medication over no pharmacological therapy to ameliorate comorbidities and improve physical activity in adults with BMI ≥30 kg/m² or BMI ≥27 kg/m² with at least one comorbid condition. It is triggered when a clinician asks, for example, 'Should I add medication to help maintain weight loss in this patient with BMI 31 and diabetes?' or 'Is pharmacotherapy appropriate for long‑term weight control in a patient with BMI 28 and hypertension?'.

This skill should be used when the user wants to "dca into" a token, "buy X every day", set up a "recurring buy", "dollar cost average" into an asset, "schedule a buy", or "auto-buy on a dip". Buys a fixed amount into a token on a schedule, optionally only when a condition holds (for example only when ETH is below a price threshold). The host agent's scheduler wakes the skill on a cadence; each wake is one self-contained run.

Use esta competência ao trabalhar com matemática simbólica em Python. Esta competência deve ser usada para tarefas de computação simbólica incluindo resolução de equações algebraicamente, realização de operações de cálculo (derivadas, integrais, limites), manipulação de expressões algébricas, trabalho com matrizes simbolicamente, cálculos de física, problemas de teoria dos números, computações de geometria e geração de código executável a partir de expressões matemáticas. Aplique esta competência quando o usuário precisa de resultados simbólicos exatos em vez de aproximações numéricas, ou ao trabalhar com fórmulas matemáticas que contêm variáveis e parâmetros.

The on-ramp for any Built GTM analyst skill when your tools are not connected yet. Tells you exactly what to paste or upload to run a given analysis today, in plain language, then hands the data to the right skill. Trigger on "I haven't connected my tools", "how do I run this without connecting", "what do I paste", "run this on my data", "I have a CSV", "bring my own data", or any moment a connector-dependent skill needs data and nothing is connected.

Lazyweb is the design-evidence skill for AI coding agents. Use it when designing, critiquing, or changing product UI — it provides real app screenshots, competitor references, best practices, quick examples, creative cross-category ideas, paywall optimization guidance, and mobile growth + monetization A/B test context. Routes to the right Lazyweb mode (design workflow, quick search, update, flowchart, or A/B test research) using MCP tools and the Lazyweb server at https://www.lazyweb.com/mcp. Use before designing any screen when you need design evidence instead of training-data vibes.

Supervises theses and dissertations end to end — structure guidance from proposal through defense, chapter-by-chapter writing support (introduction, literature review, methodology, results, discussion), supervision strategies, committee management, defense and viva voce preparation, timeline planning, feedback integration, examiner-expectation guidance, and formatting (APA 7, Chicago, university styles). Use when the request mentions thesis, dissertation, supervision, defense preparation, viva, proposal defense, thesis structure, thesis chapter, literature review chapter, methodology chapter, results chapter, discussion chapter, thesis timeline, committee, thesis formatting, or dissertation proposal. Part of the AlterLab Academic Skills suite.

Compress an oversized SKILL.md to under 200 lines without losing effectiveness. Load when a skill exceeds 200 lines, when AGENTS.md triggers compression after a skill edit, or when the user asks to compress, shrink, slim down, or optimize a skill. Also triggers on "this skill is too long", "reduce skill size", "make this skill shorter". Applies to all skills including meta skills — the 200-line rule has no exceptions. Preserves hard gates, gotchas, output format, routing triggers, and at least one example. When genuinely CORE content cannot be compressed away, invokes split-skill instead of degrading the skill.

Starlette 1.0 ASGI framework reference with working code examples for every feature. Use this skill whenever writing Starlette applications, building ASGI middleware, working with FastAPI internals, or writing async Python web services. Also trigger when the user mentions Starlette, ASGI, or needs help with routing, WebSockets, middleware, lifespan handlers, or test clients in the Starlette ecosystem — even if they don't name Starlette explicitly but are clearly working with it (e.g., importing from starlette.*, using TestClient with httpx, or writing ASGI scope/ receive/send functions). Covers the 1.0 API exclusively — all deprecated 0.x patterns have been removed.